Data Science & Machine Learning
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Join this channel to learn data science, artificial intelligence and machine learning with funny quizzes, interesting projects and amazing resources for free For collaborations: @love_data
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Network:📈 Analytical overview of Telegram channel Data Science & Machine Learning
Channel Data Science & Machine Learning (@datasciencefun) in the English language segment is an active participant. Currently, the community unites 77 282 subscribers, ranking 2 004 in the Education category and 4 033 in the India region.
📊 Audience metrics and dynamics
Since its creation on невідомо, the project has demonstrated rapid growth, gathering an audience of 77 282 subscribers.
According to the latest data from 28 August, 2026, the channel demonstrates stable activity. Although there has been a change in the number of participants by 347 over the last 30 days and by 6 over the last 24 hours, overall reach remains high.
- Verification status: Not verified
- Engagement rate (ER): The average audience engagement rate is 2.66%. Within the first 24 hours after publication, content typically collects 1.12% reactions from the total number of subscribers.
- Post reach: On average, each post receives 2 057 views. Within the first day, a publication typically gains 866 views.
- Reactions and interaction: The audience actively supports content: the average number of reactions per post is 3.
- Thematic interests: Content is focused on key topics such as learning, accuracy, distribution, panda, dataset.
📝 Description and content policy
The author describes the resource as a platform for expressing subjective opinions:
“Join this channel to learn data science, artificial intelligence and machine learning with funny quizzes, interesting projects and amazing resources for free
For collaborations: @love_data”
Thanks to the high frequency of updates (latest data received on 29 August, 2026), the channel maintains relevance and a high level of publication reach. Analytics show that the audience actively interacts with content, making it an important point of influence in the Education category.
77 282
Subscribers
+624 hours
-107 days
+34730 days
Posts Archive
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✅ Tableau Calculated Fields
What are Calculated Fields?
Custom formulas you create in Tableau to do calculations beyond default aggregations. Think: Excel formulas inside Tableau.
Why use them?
1. Create new metrics like Profit Margin, YoY Growth
2. Categorize data: High/Medium/Low sales
3. Date math: Days between orders, fiscal periods
4. Conditional logic: IF/THEN/ELSE rules
Basic Syntax
IF [Sales] > 10000 THEN "High" ELSE "Low" END
[Profit] / [Sales] → Profit Ratio
DATEDIFF('day', [Order Date], [Ship Date])
Key Functions
Logical: IF, IIF, CASE
Math: ROUND, ABS, SQRT
Date: YEAR, MONTH, DATEDIFF
String: LEFT, RIGHT, CONTAINS
Pro Tips
1. Calculated fields compute row-level or aggregate depending on formula
2. Use ATTR() to avoid aggregation errors
3. Name fields clearly: Profit Margin % not Calc1
4. Test with a few rows before using in dashboards
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👉 Tableau is one of the most popular Data Visualization and Business Intelligence (BI) tools.
It helps transform raw data into:
✔ Interactive dashboards
✔ Visual reports
✔ Business insights
🔹 1. What is Tableau?
Tableau is a drag-and-drop data visualization tool used by:
✔ Data Analysts
✔ Business Analysts
✔ Data Scientists
✔ Managers & Executives
👉 It allows users to analyze data without extensive coding.
🔥 2. Why Tableau is Popular?
✔ Easy to learn
✔ Interactive dashboards
✔ Fast visualization creation
✔ Connects to multiple data sources
🔹 3. Tableau Products
✅ Tableau Desktop: Used to create visualizations and dashboards.
✅ Tableau Server: Used to publish and share dashboards.
✅ Tableau Public: Free version for learning and sharing public dashboards.
🔹 4. Connecting Data Sources ⭐
Tableau can connect to:
✔ Excel files
✔ CSV files
✔ SQL Databases
✔ Cloud platforms
✔ APIs
🔹 5. Tableau Interface
Main areas:
✅ Data Pane: Contains fields and tables.
✅ Shelves: Used to build charts.
✅ Marks Card: Controls color, size, labels, and details.
✅ Worksheet: Area where visualizations are created.
🔥 6. Dimensions vs Measures ⭐
Dimensions: Categorical data.
Examples: ✔ Region, ✔ Product, ✔ Customer Name
Measures: Numerical data.
Examples: ✔ Sales, ✔ Profit, ✔ Quantity
🔹 7. Common Charts in Tableau
✔ Bar Chart
✔ Line Chart
✔ Pie Chart
✔ Map
✔ Scatter Plot
✔ Heat Map
🔹 8. Filters in Tableau
Filters help users focus on specific data.
Example:
✔ View sales for only one region,
✔ Show data for a selected year
🔹 9. Dashboards in Tableau ⭐
A dashboard combines multiple charts into one screen.
Example:
📊 Sales Trend,
📈 Profit Analysis,
🌍 Regional Performance
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✔ Common in analytics jobs
✔ Great for storytelling with data
✔ Frequently asked in interviews
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